rm(list=setdiff(ls(), "twd")) 
library(fixest);library(AER);library(stringr)
options(warn=-1)


data<-readRDS(paste(twd,"data/made_data/vreg_wgeos_race.rds",sep=""))

## In person 20
data$in_person_primary_20<-ifelse(data$voting_method_200303 == "P",1,0)
## Abs early 20
data$abs_early_primary_20<-ifelse(data$voting_method_200303 %in% c("A","E"),1,0)
## In person 18
data$in_person_general_18<-ifelse(data$voting_method_181106 == "P",1,0)
## Abs early 18
data$abs_early_general_18<-ifelse(data$voting_method_181106 %in% c("A","E"),1,0)
## Take First Difference
data$diff_in_person<-data$in_person_primary_20-data$in_person_general_18
data$diff_abs_early<-data$abs_early_primary_20-data$abs_early_general_18
### get the minimum of the distance to a consolidated (including super sites)
data$distance_realized_min<-apply(cbind(data$distance_realized,data$distancegov1,data$distancegov2),1,min,na.rm=T)
## Difference between assigned and realized distances (in logs and levels)
data$ln_dist_change<-ifelse(data$moved==1,log(data$distance_realized_min)-log(data$distance_assigned),0)
data$lev_dist_change<-ifelse(data$moved==1,data$distance_realized_min-data$distance_assigned,0)
### Difference between assigned and realized size # of assigned voters (in logs and levels)
data$ln_diff_N<-log(data$realized_N)-log(data$assigned_N)
data$lev_diff_N<-data$realized_N-data$assigned_N

#### Create differences in turnout for all previous elections and run regression ######

## 18-18b

data$in_person_primary_18<-ifelse(data$voting_method_180802== "P",1,0)
data$abs_early_primary_18<-ifelse(data$voting_method_180802 %in% c("A","E"),1,0)

data$diff_in_person_18_18<-data$in_person_general_18-data$in_person_primary_18
data$diff_abs_early_18_18<-data$abs_early_general_18-data$abs_early_primary_18

## 18-16

data$in_person_general_16<-ifelse(data$voting_method_161108== "P",1,0)
data$abs_early_general_16<-ifelse(data$voting_method_161108 %in% c("A","E"),1,0)

data$diff_in_person_18_16<-data$in_person_primary_18-data$in_person_general_16
data$diff_abs_early_18_16<-data$abs_early_primary_18-data$abs_early_general_16

## 16-16a

data$in_person_primary_16a<-ifelse(data$voting_method_160804== "P",1,0)
data$abs_early_primary_16a<-ifelse(data$voting_method_160804 %in% c("A","E"),1,0)

data$diff_in_person_16_16a<-data$in_person_general_16-data$in_person_primary_16a
data$diff_abs_early_16_16a<-data$abs_early_general_16-data$abs_early_primary_16a

## 16a-16b

data$in_person_primary_16b<-ifelse(data$voting_method_160301== "P",1,0)
data$abs_early_primary_16b<-ifelse(data$voting_method_160301 %in% c("A","E"),1,0)


data$diff_in_person_16_16b<-data$in_person_primary_16a-data$in_person_primary_16b
data$diff_abs_early_16_16b<-data$in_person_primary_16a-data$abs_early_primary_16b

## 16b-14

data$in_person_general_14<-ifelse(data$voting_method_141104== "P",1,0)
data$abs_early_general_14<-ifelse(data$voting_method_141104 %in% c("A","E"),1,0)

data$diff_in_person_16_14<-data$in_person_primary_16b-data$in_person_general_14
data$diff_abs_early_16_14<-data$in_person_primary_16b-data$abs_early_general_14

## 14-14a

data$in_person_primary_14<-ifelse(data$voting_method_140807== "P",1,0)
data$abs_early_primary_14<-ifelse(data$voting_method_140807 %in% c("A","E"),1,0)

data$diff_in_person_14_14<-data$in_person_general_14 - data$in_person_primary_14
data$diff_abs_early_14_14<-data$abs_early_general_14 - data$abs_early_primary_14

## 14a-12

data$in_person_general_12<-ifelse(data$voting_method_121106== "P",1,0)
data$abs_early_general_12<-ifelse(data$voting_method_121106 %in% c("A","E"),1,0)

data$diff_in_person_14_12<-data$in_person_primary_14 - data$in_person_general_12
data$diff_abs_early_14_12<-data$abs_early_primary_14 - data$abs_early_general_12



### Length of unique ops
lu<-function(x){length(unique(x))}


## Get  Dem votes
dem_votes<-function(x){ 
  sum( ifelse(str_trim(x) %in% c("DG","D"),1,0 ))
}

## Get  Rep votes
rep_votes<-function(x){ 
  sum( ifelse(str_trim(x) %in% c("RG","R"),1,0 ))
}

## Get All votes
total_votes<-function(x){
  sum(x)
}

## Get Dem/Rep Votes for each
data$dem_primary_votes<-apply(data[,c("party_voted_180802","party_voted_160804", "party_voted_160301","party_voted_140807")],1, dem_votes)
data$rep_primary_votes<-apply(data[,c("party_voted_180802","party_voted_160804", "party_voted_160301","party_voted_140807")],1, rep_votes)

## Absentee 
votes_abs<-c("abs_early_primary_18","abs_early_general_16","abs_early_primary_16a","abs_early_primary_16b","abs_early_general_14","abs_early_primary_14","abs_early_general_12")
## In Person
votes_in<-c("in_person_primary_18","in_person_general_16","in_person_primary_16a","in_person_primary_16b","in_person_general_14","in_person_primary_14","in_person_general_12")
## Absentee | Primary
primary_abs<-c("abs_early_primary_18","abs_early_primary_16a","abs_early_primary_16b","abs_early_primary_14")
## In Person | Primary
primary_in<-c("in_person_primary_18","in_person_primary_16a","in_person_primary_16b","in_person_primary_14")

### Get each of these for the individual
data$all_votes<-apply(data[,c(votes_abs,votes_in)],1, total_votes)
data$primary_votes<-apply(data[,c(primary_abs,primary_in)],1, total_votes)
data$general_votes<-data$all_votes- data$primary_votes





## Create race
data$white<-ifelse(data$race_mod2=="White",1,0)
data$black<-ifelse(data$race_mod2=="Black",1,0)
data$hispanic<-ifelse(data$race_mod2=="Hispanic",1,0)
data$asian<-ifelse(data$race_mod2=="Asian",1,0)
## Female indicator
data$female<-ifelse(str_trim(data$cde_gender)=="F",1,0)

covs<-c("moved","consolidated","distance_assigned","distance_realized_min","assigned_N","realized_N",
        "white","black","asian","hispanic", "inc_est","female", "in_person_primary_20","abs_early_primary_20",
        "in_person_general_18","abs_early_general_18", "all_votes","general_votes","primary_votes")


descripts_fun<-function(dat,x){
  out<-c(round(mean(dat[,x],na.rm=T),3),"&",round(median(dat[,x],na.rm=T),3),"&",round(sd(dat[,x],na.rm=T),3),"&",
         nrow(dat)-sum(is.na(dat[,x])),"\\")
  return(out)
}


descripts<-data.frame(matrix("NA",length(covs),8))

for(i in 1:length(covs)){
  descripts[i,]<-descripts_fun(data,covs[i])
}

descripts<-cbind(covs,descripts)


descripts<-rbind(descripts[1:3,], 
                 c(covs[3],descripts_fun(data[data$moved==1,], "distance_assigned")),
                 descripts[4,],
                 c(covs[4],descripts_fun(data[data$moved==1,],"distance_realized_min")),
                 descripts[5,],
                 c(covs[5], descripts_fun(data[data$consolidated==1,],"assigned_N")),
                 descripts[6,],
                 c(covs[6],descripts_fun(data[data$consolidated==1,],"realized_N")),
                 descripts[7:nrow(descripts),]
)

log_print(descripts,row.names = F)
